Monitoring cardiac events is of clinical importance in the early detection of potentially fatal conditions such as atrial fibrillation (AF or A-fib). Current technologies involve contact sensors such as Holter monitors the individual must wear constantly for detecting A-fib episodes. Such a requirement can lead to patient discomfort, dependency, loss of dignity, and further may fail due to a variety of reasons including refusal to wear the monitoring device. In A-fib patients, the variability in beat-to-beat intervals can be large and can lead to many spectral components. Hence detecting rate can be inaccurate and is not going to help in detecting cardiac arrhythmia effectively.
Accordingly, what is needed in this art are increasingly sophisticated systems and methods for processing a time-series signal generated from video captured of a subject to obtain a continuous PPG signal from which beat-to-beat time intervals can be reliably extracted and viewed without disturbing the resting cardiac patient.